Update README.md

README.md

@@ -1,21 +1,21 @@
 ---
-language: en
-library_name: audiocraft
-tags:
-- text-to-audio
-- musicgen
 inference: true
 pipeline_tag: text-to-audio
+library_name: audiocraft
 widget:
   - text: hip hop, soul, piano, chords, jazz, neo jazz, G# minor, 140 bpm
     example_title: Prompt 1
   - text: music, hip hop, soul, rnb, neo soul, C# major, 80 bpm
     example_title: Prompt 2
+language: en
+tags:
+- text-to-audio
+- musicgen
 ---
 
-# Model Card for songstarter-v0.1
+# Model Card for musicgen-songstarter-v0.1
 
-songstarter-v0.1 is a MusicGen 32k model fine-tuned on a dataset of hip-hop/rap/trap/rnb/soul melody loops. It's intended to be used to generate song ideas that are useful for music producers.
+musicgen-songstarter-v0.1 is a MusicGen 32k model fine-tuned on a dataset of hip-hop/rap/trap/rnb/soul melody loops. It's intended to be used to generate song ideas that are useful for music producers.
 
 This is a proof of concept. Hopefully, we will be able to collect more data and train a better models in the future.
 
@@ -32,7 +32,7 @@ Then, you should be able to load this model just like any other musicgen checkpo
 ```python
 from audiocraft.models import musicgen
 
-model = musicgen.MusicGen.get_pretrained('nateraw/songstarter-v0.1', device='cuda')
+model = musicgen.MusicGen.get_pretrained('nateraw/musicgen-songstarter-v0.1', device='cuda')
 ```
 
 To generate and save audio samples, you can do:
@@ -45,7 +45,7 @@ from audiocraft.models import musicgen
 from audiocraft.data.audio import audio_write
 from audiocraft.utils.notebook import display_audio
 
-model = musicgen.MusicGen.get_pretrained('nateraw/songstarter-v0.1', device='cuda')
+model = musicgen.MusicGen.get_pretrained('nateraw/musicgen-songstarter-v0.1', device='cuda')
 
 # path to save our samples.
 out_dir = Path("./samples")